Hasan Fallahgoul

Scale-Insensitive Neural Network Significance Tests

2025 · arXiv (Cornell University)

This paper develops a scale-insensitive framework for neural network significance testing, substantially generalizing existing approaches through three key innovations. First, we replace metric entropy calculations with Rademacher complexity bounds, enabling the analysis of neural networks …